1. Field of the Invention
The present invention relates to white balance technology that corrects images so that white objects, the colors of which vary with the light source (illumination) when the images are captured using digital cameras, appear white.
2. Description of the Related Art
In general, a human's eyes have the ability to adaptively recognize the colors of object as the original colors thereof regardless of the light source. In contrast, digital cameras distort the original colors of objects depending on the light source that is used when images of the objects are acquired.
For example, when a white object (an object having a white color) is captured in an environment in which the color temperature of the light source is low, an image having a red tint is acquired. In contrast, in an environment in which color temperature is high, an image having a blue tint is acquired. Illumination devices that people use in daily lives have different color temperatures according to the type thereof, and the same solar light varies in color temperature over the passage of time, such as the morning or afternoon. As a result, in the case of digital cameras having no ability to adapt to the colors of light sources, unlike humans, the colors of acquired images differ from the actual colors thereof due to the image acquisition environment. Accordingly, white balance is required for digital cameras.
In general, the term “white balance” in digital cameras refers to the adjustment of optical or electrical gain to form a specific energy distribution of respective wavelengths of R, G, and B under a specific color temperature condition in the case where the energy distribution of R, G and B varies with the color temperature.
Recently marketed digital cameras adopt an ‘auto white balance’ function, which refers to a function of, when an image is input to the image sensor of a digital camera, analyzing the image and automatically performing white balance without requiring any manipulation on the part of a user.
The effective performance of such auto white balance is dependent on the type of information of an image, acquired through an image sensor, that is used.
Conventional auto white balance methods include a first method of averaging the RGB values of the entire input image or a predetermined part of an image (for example, a region that is in focus) and adjusting a ratio so that the RGB values have the same value, a second method of searching for a white color region of an input image and taking the color in the found region as the color of the light source, and a third method of performing conversion to another color space and utilizing the statistical characteristics of the color signals of an image.
The above-described conventional auto white balance methods are based on assumptions that are made about the color distribution of an image. For images that do not satisfy the set assumptions, the white balance fails or is not performed effectively.
For example, in the case of the first method, an accurate white balance cannot be performed if color distribution is not varied in an acquired image, in the case of the second method, white balance fails if no white color region is present, and, in the case of the third method, the accuracy of white balance is considerably decreased if color distribution is not sufficient in an image or if some colors occupy an excessively large area in proportion to the size of an image.